Versatile Stimulation Back-End With Programmable Exponential Current Pulse Shapes for a Retinal Visual Prosthesis
Bibliographic record
Abstract
This paper reports on the design, implementation, and test of a stimulation back-end, for an implantable retinal prosthesis. In addition to traditional rectangular pulse shapes, the circuit features biphasic stimulation pulses with both rising and falling exponential shapes, whose time constants are digitally programmable. A class-B second generation current conveyor is used as a wide-swing, high-output-resistance stimulation current driver, delivering stimulation current pulses of up to ±96 μA to the target tissue. Duration of the generated current pulses is programmable within the range of 100 μs to 3 ms. Current-mode digital-to-analog converters (DACs) are used to program the amplitudes of the stimulation pulses. Fabricated using the IBM 130 nm process, the circuit consumes 1.5×1.5 mm2of silicon area. According to the measurements, the DACs exhibit DNL and INL of 0.23 LSB and 0.364 LSB, respectively. Experimental results indicate that the stimuli generator meets expected requirements when connected to electrode-tissue impedance of as high as 25 k Ω. Maximum power consumption of the proposed design is 3.4 mW when delivering biphasic rectangular pulses to the target load. A charge pump block is in charge of the upconversion of the standard 1.2-V supply voltage to ±3.3V.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".